The present invention, in some embodiments thereof, relates to treatment of a patient and, more specifically, but not exclusively, to systems and methods for treatment of a patient by automated patient care.
Certain patients require assistance with feeding via an enteral approach, require assistance with breathing, and/or require assistance with urination, for example, patients in the intensive care unit (ICU) which may be sedated and/or intubated. Current approaches are based on a manual assessment (e.g., by a nurse, physician), and are limited in their ability to provide optimal settings for the patient. Medical outcomes of patients may be improved by better control of enteral feeding, breathing, and/or urination.
Recent studies suggest that nutritional guidelines across the majority of intensive care units (ICUs) are not being implemented, for example, as described with reference to Bendavid I, Singer P, Theilla M, et al. (2017) NutritionDay ICU: a 7-year worldwide prevalence study of nutrition practice in intensive care. Clin Nutr 36:1122-1129, and Heyland D K, Schroter-Noppe D, Drover J W, Jain M, Keefe L, Dhaliwal R, Day A (2003) Nutrition support in the critical care setting: current practice in Canadian ICUs—opportunities for improvement? J Parenter Enteral Nutr. 27:74-83. Lack of knowledge, no technology to support medical staff, and general noncompliance with nutritional guidelines result in higher mortality and infection complications.
One of the main pitfalls is the common use of predictive equations like Harris-Benedict equations for targeting energy prescription in critical illness. The equations have been demonstrated by many, for example, as described with reference to Zusman O, Kagan I, Bendavid I, Theilla M, Cohen J, Singer P (2018) Predictive equations Predictive Equations versus Measured Energy Expenditure by Indirect calorimetry: A Retrospective Validation. Clin Nutr (Article in Press, and Tatucu-Babet O A, Ridley E J, Tierney A C (2015) The prevalence of underprescription or overprescription of energy needs in critically ill mechanically ventilated adults as determined by indirect calorimetry: a systematic literature review. JPEN J Parenteral Enteral Nutr 40:212-225, to be inaccurate in more than 50% of the cases, leading to under or over nutrition. In case of too low a target, patients will be underfed and, since the process is progressively increasing the rate of administration, calorie balance will reach large negative values that are associated with increased morbidity, for example, as described with reference to Dvir D, Cohen J, Singer P (2005) Computerized energy balance and complications in critically ill patients: an observational study. Clin Nutr 25:37-44.
Providing higher calories target that is needed has been found to be associated with increased mortality, for example, as described with reference to Zusman O, Theilla M, Cohen J, Kagan I, Bendavid I, Singer P (2016) Resting energy expenditure, calorie and protein consumption in critically ill patients: a retrospective cohort study. Crit Care 20:367, resulting in recommendations by ESPEN to measure energy expenditure in a rested condition [REE], for example, as described with reference to Singer P, Reintam Blaser A, M Berger M M, Alhazzani W, Calder P C, Casaer M (2018) ESPEN guideline on clinical nutrition in the intensive care unit. Clin Nutr Epub ahead of publication. 